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Vivek N. Mahale, Jerald A. Brotzge, and Howard B. Bluestein

Abstract

Adding a mix of X- or C-band radars to the current Weather Surveillance Radar-1988 Doppler (WSR-88D) network could address several limitations of the network, including improvements to spatial gaps in low-level coverage and temporal sampling of volume scans. These limitations can result in missing critical information in highly dynamic events, such as tornadoes and severe straight-line wind episodes. To evaluate the potential value of a mixed-band radar network for severe weather operations, a case study is examined using data from X- and S-band radars. On 13 May 2009, a thunderstorm complex associated with a cold front moved southward into southwest Oklahoma. A tornado rapidly developed from an embedded supercell within the complex. The life cycle of the tornado and subsequent wind event was sampled by the experimental Collaborative Adaptive Sensing of the Atmosphere (CASA) radar testbed of four X-band radars as well as two operational WSR-88Ds. In this study, the advantages of a mixed-band radar network are demonstrated through a chronological analysis of the event. The two radar networks provided enhanced overall situational awareness. Data from the WSR-88Ds provided 1) clear-air sensitivity, 2) a broad overview of the storm complex, 3) a large maximum unambiguous range, and 4) upper-level scans up to 19.5°. Data from the CASA radars provided 1) high-temporal, 1-min updates; 2) overlapping coverage for dual-Doppler analysis; and 3) dense low-level coverage. The combined system allowed for detailed, dual- and single-Doppler observations of a wind surge, a mesocyclone contraction, and a downburst.

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Vivek N. Mahale, Jerald A. Brotzge, and Howard B. Bluestein

Abstract

On 2 April 2010, a developing quasi-linear convective system (QLCS) moved rapidly northeastward through central Oklahoma spawning at least three intense, mesoscale vortices. At least two of these vortices caused damage rated as category 0 to 1 on the enhanced Fujita scale (EF0–EF1) in and near the town of Rush Springs. Two radar networks—the National Weather Service Weather Surveillance Radar-1988 Doppler network (WSR-88D) and the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radar network—collected high spatial and temporal resolution data of the event. This study is an in-depth polarimetric analysis of mesovortices within a QLCS. In this case study, the storm development and evolution of the QLCS mesovortices are examined. Significant findings include the following: 1) The damage in Rush Springs was caused by a combination of the fast translation speed and the embedded circulations associated with QLCS vortices. The vortices’ relative winds nearly negated the storm motion to the left of the vortex, but doubled the ground-relative wind to the right of the vortex. 2) A significant differential reflectivity (Z DR) arc developed along the forward flank of the first vortex. The Z DR arc propagated northeastward along the QLCS with the development of each new vortex. 3) A minimum in the copolar correlation coefficient (ρ hv) in the center of the strongest vortex was observed, indicating the likely existence of a polarimetric tornado debris signature (TDS). A secondary ρ hv minimum also was found just to the right of the vortex center, possibly associated with lofted debris from straight-line winds.

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Jerald A. Brotzge, Steven E. Nelson, Richard L. Thompson, and Bryan T. Smith

Abstract

The ability to provide advanced warning on tornadoes can be impacted by variations in storm mode. This research evaluates 2 yr of National Weather Service (NWS) tornado warnings, verification reports, and radar-derived convective modes to appraise the ability of the NWS to warn across a variety of convective modes and environmental conditions. Several specific hypotheses are considered: (i) supercell morphologies are the easiest convective modes to warn for tornadoes and yield the greatest lead times, while tornadoes from more linear, nonsupercell convective modes, such as quasi-linear convective systems, are more difficult to warn for; (ii) parameters such as tornado distance from radar, population density, and tornado intensity (F scale) introduce significant and complex variability into warning statistics as a function of storm mode; and (iii) tornadoes from stronger storms, as measured by their mesocyclone strength (when present), convective available potential energy (CAPE), vertical wind shear, and significant tornado parameter (STP) are easier to warn for than tornadoes from weaker systems. Results confirmed these hypotheses. Supercell morphologies caused 97% of tornado fatalities, 96% of injuries, and 92% of damage during the study period. Tornado warnings for supercells had a statistically higher probability of detection (POD) and lead time than tornado warnings for nonsupercells; among supercell storms, tornadoes from supercells in lines were slightly more difficult to warn for than tornadoes from discrete or clusters of supercells. F-scale intensity and distance from radar had some impact on POD, with less impact on lead times. Higher mesocyclone strength (when applicable), CAPE, wind shear, and STP values were associated with greater tornado POD and lead times.

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